A universal dynamical metabolic model representing mixotrophic growth of Chlorella sp. on wastes. (1st February 2023) - Pessi, Bruno Assis; Baroukh, Caroline; Bacquet, Anais; Bernard, Olivier
Abstract: An emerging idea is to couple wastewater treatment and biofuel production using microalgae to achieve higher productivities and lower costs. This paper proposes a metabolic modeling of Chlorella sp. growing on fermentation wastes (blend of acetate, butyrate and other acids) in mixotrophic conditions, accounting also for the possible inhibitory substrates. This model extends previous works by modifying the metabolic network to include the consumption of glycerol and glucose by Chlorella sp., with the goal to test the addition of these substrates in order to overcome butyrate inhibition. The metabolic model was built using the DRUM framework and consists of 188 reactions and 173 metabolites. After a calibration phase, the model was successfully challenged with data from 122 experiments collected from scientific literature in autotrophic, heterotrophic and mixotrophic conditions. The optimal feeding strategy estimated with the model reduces the time to consume the volatile fatty acids from 16 days to 2 days. The high prediction capability of this model opens new routes for enhancing design and operation in waste valorization using microalgae. Highlights: A metabolic model for Chlorella growing mixotrophically in wastes is validated. Unprecedented level of validation using 122 experiments, more than 2600 data points. Model accounts for heterotrophic growth on glycerol, glucose, acetate and butyrate. Optimal feeding conditions can reduce waste treatment time from 16 to 2 days. This model open new routes for waste valorization using microalgae.